Conference Program of WCICA 2012

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Conference Program WCICA 2012 the guidance laws mentioned above are applied to derive decentralized control laws for pursuer convoy. The results of simulation indicate the feasibility and effectiveness of the proposed algorithm. ◮ FrB11-5 17:10–17:30 Design of Networked Air Defense Fire Control Simulation System based on BOM, pp.3214–3219 Chen, Shi-jun Zhang, Juan Chen, Chen School of Automation Beijing Inst. of Tech. Tsinghua Univ. Networked air defense fire control simulation system featured with complicated interactions, varied system structure etc, and is usually faced with some difficulties in its development, such as the low capability of model reuse, the lack of regulations for model development and inflexible modification of federation. To overcome the difficulties, a framework in hierarchy of networked air defense fire control simulation system is constructed according to BOM development standard, and the component method for designing the basic model, compound model and federate is proposed, which effectively improved the efficiency of system development and the capability of model reuse. This method is not only applicable to the design of networked air defense fire control system, but also to the design of other simulation system with polytropic structure. ◮ FrB11-6 17:30–17:50 An ant colony algorithm for permutation flow shop problem, pp.596–600 Shang, Ke State Key Laboratory for Manufacturing Sys. Engineering, Xi’an Jiaotong Univ. Feng, Zuren Ke, Liangjun Xi’an Jiaotong Univ. Sys. engineering Inst. In this paper, a new ant colony optimization algorithm, called finite grade ant colony optimization, is proposed to solve permutation flow shop problem, its main characteristic is that the updated quantities of pheromone trails are independent of objective function values, and the heuristic information provide by Moccellin is adopted. The developed algorithm has been applied to the benchmark problems given by Taillard, Comparison results demonstrate that the performance of the proposed algorithm is promising. Poster Session PFrA July 6, 13:30-14:50 Chair: Duan, Guang-Ren Harbin Inst. of Tech. Co-Chair: Huo, Wei Beijing Univ. of Aeronautics & Astronautics ◁ PFrA-01 Research on Indoor Location Technology Based on RSSI and Back Propagation Neural Network , pp.80–83 Zhang, Huiqing Shi, Xiaowei Beijing Univ. of Tech. Beijing Univ. of Tech. Indoor wireless location Based on RSSI (received signal strength indicator) firstly need to determine the parameters A and N of the RSSI-d relation model. In the conventional method, the parameters A and N is subjectively designated based on experience and positioning environment, this lead to inaccurate, low precision, and weak universal. Based on a large number of RSSI-d experimental data, a totally new method using BP neural network to fit RSSI-d relationship curve is proposed. Input RSSI value into the BP input layer, we can get distance value at the output layer, then the Taylor Series expansion algorithm is used to determine the coordinates of the blind node. Finally, compared with the traditional positioning algorithms ,the experiment result shows that the new algorithm improves the positioning accuracy and universality. ◁ PFrA-02 AUTO DRAVCNC PROCESSING DATA INQUIRY SYSTEM, pp.196– 198 Liu, Hongjun Men, Xiyao Shenyang Aerospace Univ. Shenyang Aerospace Univ. The final product is often organized in the way of assembly in process of mechanical design. The assembly body generally contains many parts, which structure is affected by several main parameters, and some parameters among those parts should in keeping with each other. The paper presents a method to do it by the UG OPEN API redevelop interface. By providing parameters extraction dialog, the main parameters of the UG assembly model are extracted from model. Then the parameters can be changed in PDM . Through the traverse the way for the assembly and all parts of the body automatic update drive, avoiding one of the documents by change travel, leakage change, and wrong which result into products design problem. After synchronous update, each drawing is outputted in the way of CGM file. ◁ PFrA-03 Further Understanding of the Meaning of Fuzzy Multi-stage Conditional Statements, pp.251–254 Yu, Fusheng Wang, Xiao Beijing Normal Univ. Beijing Normal Univ. When building fuzzy inference engine, a group of fuzzy rules are given in advance, which are usually called fuzzy multi-stage conditional statements. These fuzzy multi-stage conditional statements can be divided into two categories. One type of fuzzy multi-stage conditional statements is linked by “if-else”; while the other is not. In literature, researchers usually did not distinguish the forms of them. In our opinion, these two kinds of fuzzy multi-stage conditional statements have different meanings, and this will influence the true value domain of them. In this paper, we will probe into the meaning of these two types of fuzzy multi-stage conditional statements, and discuss how to build their true value domains. ◁ PFrA-04 Architecture and Cooperation Mechanism of MAS for Information Integration Emergency-Service Oriented, pp.341–345 Yu, Haixin Chen, Jie Zhang, Juan Beijing Inst. of Tech. Beijing Inst. of Tech. Beijing Inst. of Tech. Emergency system denoted in this paper aims to harness natural disasters via investigating the situation of disasters and making contingency plans. Hence, integrating information of disasters from a complex distributed network is the foundation of the emergency system. This paper focuses on how to integrate information rapidly though multi-agent system technology. Based on this, we proposes a hierarchical architecture which organizes immense amount of information efficiently and the cooperation mechanism based on task auction. Furthermore, we build feature space to measure the information resource’s capability of supplying information, and evaluate the architecture and cooperation mechanism through its application in integrating information of a geological disaster. ◁ PFrA-05 Migration & Competition-based Particle Swarm Optimization for Parameter Estimation, pp.590–595 Ren, Ziwu Soochow Univ. Enlightened by some knowledge of ecology and swarm competition, an improved multigrouped particle swarm optimization based on migration and competition, namely PSOMC, is proposed for parameters estimation of non-linear systems. The PSOMC is not concerned with the evolution of a single population, but instead is concerned with the evolution of multiple parallel swarms; moreover it incorporates some concepts, such as reintroduction, swarm competition, adjustment of swarm size, migration of particles between the swarm, and recycling, to enhance the global exploration ability and the local exploitation capability. Numerical simulations of two benchmark functions are used to test the performance of PSOMC. Furthermore, simulation on three different kinds of models is given to illustrate the effectiveness and efficiency of the proposed parameters estimation scheme. ◁ PFrA-06 Research on the Machine Tool Selection of RMS, pp.623–627 Zhou, Fengxu Li, Aiping Xu, Liyun Tongji Univ. tongji Univ. tongji Univ. 110
WCICA 2012 Book of Abstracts: Friday Sessions Xie, Nan Tongji Univ. According to production tasks, making manufacturing resources reconstruction via machine tool selection is one of the key issues to achieve manufacturing system reorganization. At the time when machine tool is selected, qualitative factors and quantitative factors must be considered. In order to solve the problem well, the evaluation index system with a hierarchical structure was presented. A multi-objective optimization model was established, and then the model was analyzed by using hierarchical weighting methods. Finally, a practical application was provided to illustrate the scientific validity of the model and the effectiveness of the methodology. ◁ PFrA-07 A Hybrid Method for Short-term Load Forecasting in Power System, pp.696–699 Zhu, Xianghe Qi, Huan Huang, Xuncheng Sun, Suqin Huazhong Univ.of Sci. & Tech.Wuchang Branch huazhong Univ. of Sci. & Tech. Electric Power of HeNan Electric Power of HeNan In order to improve the accuracy of power load forecasting, this paper proposes a hybrid model based on Ensemble Empirical Mode Decomposition (EEMD), least square-support vector machine (SVM) and BP nature network as a short-term load forecasting model. At first, the actual power load series is decomposed into different new series based on EEMD. Then the right parameters and kernel functions are chosen to build different LS-SVM model respectively, to forecast each intrinsic mode functions, due to the change regulation of each of all resulted intrinsic mode functions. Finally, we use the BP network to reconstruct the forecasted signals of the components and obtain the ultimate forecasting results. Simulation results show that the proposed forecasting method possesses accuracy. ◁ PFrA-08 Group Decision-Making Based Case Retrieval and Its Application, pp.773–778 Zhang, Chun-xiao YAN, Aijun Zhao, Hui Wang, Pu Beijing Univ. of Tech. Beijing Univ. of Tech. Beijing Univ. of Tech. Beijing Univ. of Tech., China The distribution of the case feature attribute weights directly affects the case retrieval result. Aim at improving the retrieval precision, a retrieval method is proposed based on group decision-making for optimizing the case feature attributes weights. Firstly, multiple groups of initial weights are obtained by genetic algorithm. Then, the multiple sets of retrieval results produced by these weights are optimized through group decision-making method, and the weights can be dynamic adjusted through the deviations between individual decision results and group result. The simulation results indicate that the proposed approach can fully excavate the potential knowledge of attribute weights and thus result in higher retrieval accuracy in a case-based reasoning system. The PID adjusting comparison experiment of typical two order delay system verifies the effectiveness of the new method. ◁ PFrA-09 Attribute Reduction Method Using Water-Filling Principle for Case- Based Reasoning, pp.779–782 Zhao, Hui YAN, Aijun Zhang, Chun-xiao Wang, Pu Beijing Univ. of Tech. Beijing Univ. of Tech. Beijing Univ. of Tech. Beijing Univ. of Tech., China As the large number of feature attributes in Case-based reasoning system (CBR) brings a huge information redundancy which reduces the retrieval efficiency, a novel reduction method based on Water-Filling is proposed to remove those unnecessary attributes. In the method, the importance of each attribute could be calculated by utilizing the ratio of the standard deviation and the mean value of each attribute data as evaluation parameter, and the impotance result of each attribute is then used to guide the reduction process. The experiments on glass identification showed that the new method could get a better retrieval accuracy as well as a greater efficiency compared with the methods which do not conduct the reduction process. ◁ PFrA-10 Application of Self-organizing Feature Map Neural Network Based on Data Clustering, pp.797–802 Hu, Xiang Yang, Yun Zhang, Lihong Xiang, Tao Hong, Chengqiu Zheng, Xiaotong Tsinghua Univ. Tsinghua Univ. Tinghua Univ. Tsinghua Univ. Tsinghua Univ. Tsinghua Univ. Outlier detection is of much importance in preprocessing of data collected from complex industry system, for the data has strong nonlinearity and poor stability, involving much noise. Outlier detection based on clustering, rejects abnormal data points which have significant difference from others according to the definition of similarity. Self-organizing Feature Map (SOM) Neural Network algorithm has the self-study and adaptive functions of neural networks, so as to be a hot research in clustering analysis recently. This paper first introduces Self-organizing Feature Map algorithm based on artificial neural network, and then improves the algorithm by using weighted Euclidean distance, finally uses the software of MATLAB to analyze some actual data of electrical power. The result shows that SOM algorithm achieves a very good effect in clustering, and the MATLAB toolbox shows favorable visual effects. ◁ PFrA-11 Flow Rate Control and Resource Allocation Policy with Security Requirements in OFDMA Networks, pp.1020–1025 Zhu, Xingzheng Yue, Jianting Yang, Bo Guan, Xinping SHANGHAI JIAOTONG Univ. SHANGHAI JIAOTONG Univ. Shanghai Jiao Tong Univ. Shanghai Jiao Tong Univ. OFDMA-based network performs well in maximizing the overall throughput, and meanwhile, problems with security requirements are focused to satisfy the increasing needs of confidential data transmissions. According to information theory, however, secure transmission undesirably antagonizes larger flow rate, thus a tradeoff is expected to balance these two matters. In this paper, we consider a downlink situation in OFDMA network, where all users request secure transmission from the base station yet the resources including power and subcarriers are limited such that an appropriate policy on resource allocation can play an instrumental role. Dynamic queueing and Lyapunov optimization are two highlights in this process. We utilize dynamic queueing so that merely instantaneous state of the network is enough, which is advantageous for easier implementations. On the other hand, by the means of Lyapunov optimization, we also prove our algorithm can obtain a performance of flow rate admission extremely close to the optimal. Applying this policy can reduce computational complexity significantly but still perform close to optimality. ◁ PFrA-12 Augmented Dimension Algorithm Based on Sequential Detection for Maneuvering Target Tracking, pp.1323–1327 Pan, Baogui Peng, Dongliang Shao, Genfu Inst. of Information & Control Hangzhou Dianzi Univ. Inst. of Information & Control In order to solve the problem that target tracking algorithm based on single model has poor tracking performance when the target occurs high maneuver and that IMM algorithm has low accuracy in tracking a constant velocity target, an augmented dimension algorithm based on sequential detection for maneuvering target tracking is proposed. First, the KF-UKF joint filtering is proposed. The Kalman filter based on the CV model is used to estimate the state of a constant velocity target. When the target maneuver is detected, the dimension of the CV model is augmented, and the unscented Kalman filter is used to estimate the state. Second, a fading memory sequential detection algorithm is 111
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WCICA 2012 The 10 th World Congress
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